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How Gender and Prior Disadvantage Predict Performance in College

Author

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  • Judith M. Delaney

    (University of Bath, University College London and Institute of Labor Economics (IZA), Bonn)

  • Paul J. Devereux

    (University College Dublin, Centre for Economic Policy Research (CEPR), London, Institute of Labor Economics (IZA), Bonn, Norwegian School of Economics)

Abstract

Much research has shown that having a better class of degree has significant payoff in the labour market. Using administrative data from Ireland, we explore the performance in college of different types of students. We find that post-primary school achievement is an important predictor: its relationship with college performance is concave for college completion, approximately linear for the probability of obtaining at least second class honours, upper division, and convex for the probability of obtaining a first class honours degree. We find that females do better in college than males, even after we account for their greater prior achievement, and this is true in both non-STEM and STEM fields. Disabled students, students from disadvantaged schools, and students who qualify for means-tested financial aid are less likely to complete and less likely to obtain first class honours or a second class honours, upper division degree. However, once we control for post-primary school achievement, these students actually perform better in college than others. We also find that, conditional on prior achievement, students from private exam-oriented “grind” schools and from Irish-medium schools are less likely to finish a degree and less likely to perform well in college, possibly because their school exam results are high relative to their abilities. Our results suggest that current college policies that lower entry requirements for disabled students and students from disadvantaged backgrounds may be justified on efficiency as well as equity grounds. They also suggest that college performance might be improved by increasing entry requirements for students who come from school types that convey advantages in the post-primaryexams that determine college entry.

Suggested Citation

  • Judith M. Delaney & Paul J. Devereux, 2020. "How Gender and Prior Disadvantage Predict Performance in College," The Economic and Social Review, Economic and Social Studies, vol. 51(2), pages 189-239.
  • Handle: RePEc:eso:journl:v:51:y:2020:i:2:p:189-239
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    1. D. Flannery & J. Cullinan, 2014. "Where they go, what they do and why it matters: the importance of geographic accessibility and social class for decisions relating to higher education institution type, degree level and field of study," Applied Economics, Taylor & Francis Journals, vol. 46(24), pages 2952-2965, August.
    2. Delaney, Judith M. & Devereux, Paul J., 2019. "It's Not Just for Boys! Understanding Gender Differences in STEM," IZA Discussion Papers 12176, Institute of Labor Economics (IZA).
    3. Delaney, Judith M. & Devereux, Paul J., 2020. "Choosing differently? College application behavior and the persistence of educational advantage," Economics of Education Review, Elsevier, vol. 77(C).
    4. Jennifer A. Heissel & Emma K. Adam & Jennifer L. Doleac & David N. Figlio & Jonathan Meer, 2021. "Testing, Stress, and Performance: How Students Respond Physiologically to High-Stakes Testing," Education Finance and Policy, MIT Press, vol. 16(2), pages 183-208, Spring.
    5. Richard Murphy & Gill Wyness, 2023. "Testing Means-Tested Aid," Journal of Labor Economics, University of Chicago Press, vol. 41(3), pages 687-727.
    6. Haroon Chowdry & Claire Crawford & Lorraine Dearden & Alissa Goodman & Anna Vignoles, 2013. "Widening participation in higher education: analysis using linked administrative data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 176(2), pages 431-457, February.
    7. John Cullinan & Kevin Denny & Darragh Flannery, 2021. "A distributional analysis of upper secondary school performance," Empirical Economics, Springer, vol. 60(2), pages 1085-1113, February.
    8. Feng, Andy & Graetz, Georg, 2017. "A question of degree: The effects of degree class on labor market outcomes," Economics of Education Review, Elsevier, vol. 61(C), pages 140-161.
    9. John Cullinan & Darragh Flannery (ed.), 2017. "Economic Insights on Higher Education Policy in Ireland," Springer Books, Springer, number 978-3-319-48553-9, February.
    10. Julian R. Betts & Darlene Morell, 1999. "The Determinants of Undergraduate Grade Point Average: The Relative Importance of Family Background, High School Resources, and Peer Group Effects," Journal of Human Resources, University of Wisconsin Press, vol. 34(2), pages 268-293.
    11. Freier, Ronny & Schumann, Mathias & Siedler, Thomas, 2015. "The earnings returns to graduating with honors — Evidence from law graduates," Labour Economics, Elsevier, vol. 34(C), pages 39-50.
    12. Cohn, Elchanan & Cohn, Sharon & Balch, Donald C. & Bradley, James Jr., 2004. "Determinants of undergraduate GPAs: SAT scores, high-school GPA and high-school rank," Economics of Education Review, Elsevier, vol. 23(6), pages 577-586, December.
    13. Arulampalam, Wiji & Naylor, Robin A. & Smith, Jeremy P., 2005. "Effects of in-class variation and student rank on the probability of withdrawal: cross-section and time-series analysis for UK university students," Economics of Education Review, Elsevier, vol. 24(3), pages 251-262, June.
    14. Susan M. Dynarski, 2003. "Does Aid Matter? Measuring the Effect of Student Aid on College Attendance and Completion," American Economic Review, American Economic Association, vol. 93(1), pages 279-288, March.
    15. Claire Crawford, 2014. "Socio-economic differences in university outcomes in the UK: drop-out, degree completion and degree class," IFS Working Papers W14/31, Institute for Fiscal Studies.
    16. Denny, Kevin, 2014. "The effect of abolishing university tuition costs: Evidence from Ireland," Labour Economics, Elsevier, vol. 26(C), pages 26-33.
    17. Pastine, Ivan & Pastine, Tuvana, 2012. "Student incentives and preferential treatment in college admissions," Economics of Education Review, Elsevier, vol. 31(1), pages 123-130.
    18. Delaney, Judith M. & Devereux, Paul J., 2020. "Math matters! The importance of mathematical and verbal skills for degree performance," Economics Letters, Elsevier, vol. 186(C).
    19. Gérard Lassibille & María Lucía Navarro Gómez, 2008. "Why do higher education students drop out? Evidence from Spain," Post-Print halshs-00324365, HAL.
    20. John Cullinan & Darragh Flannery & Sharon Walsh & Selina Mccoy, 2013. "Distance Effects, Social Class and the Decision to Participate in Higher Education in Ireland," The Economic and Social Review, Economic and Social Studies, vol. 44(1), pages 19-51.
    21. Eric Bettinger, 2004. "How Financial Aid Affects Persistence," NBER Chapters, in: College Choices: The Economics of Where to Go, When to Go, and How to Pay For It, pages 207-238, National Bureau of Economic Research, Inc.
    22. Caroline M. Hoxby, 2004. "College Choices: The Economics of Where to Go, When to Go, and How to Pay For It," NBER Books, National Bureau of Economic Research, Inc, number hoxb04-1.
    23. Delaney, Judith M. & Devereux, Paul J., 2019. "Understanding gender differences in STEM: Evidence from college applications✰," Economics of Education Review, Elsevier, vol. 72(C), pages 219-238.
    24. Karsten Albæk, 2017. "Optimal admission to higher education," Education Economics, Taylor & Francis Journals, vol. 25(1), pages 60-83, January.
    25. Robin Naylor & Jeremy Smith, 2004. "Degree performance of Economics students in UK universities: absolute and relative performance in prior qualifications," Scottish Journal of Political Economy, Scottish Economic Society, vol. 51(2), pages 250-265, May.
    26. Robin Naylor & Jeremy Smith & Shqiponja Telhaj, 2016. "Graduate returns, degree class premia and higher education expansion in the UK," Oxford Economic Papers, Oxford University Press, vol. 68(2), pages 525-545.
    27. Devereux, Paul J. & Delaney, Judith, 2019. "Understanding Gender Differences in STEM: Evidence from College Applications," CEPR Discussion Papers 13558, C.E.P.R. Discussion Papers.
    28. Doris, Aedin & O'Neill, Donal & Sweetman, Olive, 2019. "Good Schools or Good Students? The Importance of Selectivity for School Rankings," IZA Discussion Papers 12459, Institute of Labor Economics (IZA).
    29. Caroline Minter Hoxby, 2004. "Introduction to "College Choices: The Economics of Where to Go, When to Go, and How to Pay For It"," NBER Chapters, in: College Choices: The Economics of Where to Go, When to Go, and How to Pay For It, pages 1-12, National Bureau of Economic Research, Inc.
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    Cited by:

    1. Judith M. Delaney & Paul J. Devereux, 2022. "Gender Differences in STEM Persistence after Graduation," Economica, London School of Economics and Political Science, vol. 89(356), pages 862-883, October.
    2. Delaney, Judith M. & Devereux, Paul J., 2021. "Gender differences in college applications: Aspiration and risk management," Economics of Education Review, Elsevier, vol. 80(C).
    3. Delaney, Judith M. & Devereux, Paul J., 2021. "Gender and Educational Achievement: Stylized Facts and Causal Evidence," IZA Discussion Papers 14074, Institute of Labor Economics (IZA).

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    More about this item

    Keywords

    gender; education; Ireland;
    All these keywords.

    JEL classification:

    • I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions
    • I24 - Health, Education, and Welfare - - Education - - - Education and Inequality
    • J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

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